Continuous molecular fields and the concept of molecular co-fields in structure–activity studies

2019 ◽  
Vol 11 (20) ◽  
pp. 2701-2713
Author(s):  
Igor I Baskin ◽  
Nelly I Zhokhova
Keyword(s):  
Molecular Design ◽  
3D Structure ◽  
Biological Targets ◽  
3D Space ◽  
Structure Of Molecules ◽  
Structure Activity ◽  
Activity Models ◽  
Molecular Fields ◽  
Physical Fields ◽  
Continuous Molecular Fields

The analysis of information on the spatial structure of molecules and the physical fields of their interactions with biological targets is extremely important for solving various problems in drug discovery. This mini-review article surveys the main features of the continuous molecular fields approach and its use for analyzing structure–activity relationships in 3D space, building 3D quantitative structure–activity models and conducting similarity based virtual screening. Particular attention is paid to the consideration of the concept of molecular co-fields and their use for the interpretation of 3D structure–activity models. The principles of molecular design based on the overlapping and the similarity of molecular fields with corresponding co-fields are formulated.

Development of Novel Glitazones as Antidiabetic Agents: Molecular Design, Synthesis, Evaluation of Glucose Uptake Activity and SAR Studies

2020 ◽  
Vol 17 (7) ◽  
pp. 840-849
Author(s):  
Mahendra Gowdru Srinivas ◽  
Prabitha Prabhakaran ◽  
Subhankar Probhat Mandal ◽  
Yuvaraj Sivamani ◽  
Pranesh Guddur ◽  
...  
Keyword(s):  
Glucose Uptake ◽  
Molecular Design ◽  
Docking Studies ◽  
Antidiabetic Activity ◽  
Design Synthesis ◽  
In Silico Docking ◽  
Ppar Γ ◽  
Sar Studies ◽  
Structure Activity ◽  
Uptake Activity

Background: Thiazolidinediones and its bioisostere, namely, rhodanines have become ubiquitous class of heterocyclic compounds in drug design and discovery. In the present study, as part of molecular design, a series of novel glitazones that are feasible to synthesize in our laboratory were subjected to docking studies against PPAR-γ receptor for their selection. Methods and Results: As part of the synthesis of selected twelve glitazones, the core moiety, pyridine incorporated rhodanine was synthesized via dithiocarbamate. Later, a series of glitazones were prepared via Knovenageal condensation. In silico docking studies were performed against PPARγ protein (2PRG). The titled compounds were investigated for their cytotoxic activity against 3T3-L1 cells to identify the cytotoxicity window of the glitazones. Further, within the cytotoxicity window, glitazones were screened for glucose uptake activity against L6 cells to assess their possible antidiabetic activity. Conclusion: Based on the glucose uptake results, structure activity relationships are drawn for the title compounds.

Classification (Agonist/Antagonist) and Regression “Structure-Activity” Models of Drug Interaction with 5-HT6

2018 ◽  
Vol 18 (3) ◽  
pp. 213-221 ◽  
Author(s):  
Oleg A. Raevsky ◽  
Veniamin Y. Grigorev ◽  
Alexander V. Yarkov ◽  
Daniel E. Polianczyk ◽  
Vadim V. Tarasov ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Structure Activity ◽  
Activity Models

scholarly journals CoeViz 2: Protein Graphs Derived From Amino Acid Covariance

2021 ◽  
Vol 1 ◽  
Author(s):  
Daniel Corcoran ◽  
Nicholas Maltbie ◽  
Shivchander Sudalairaj ◽  
Frazier N. Baker ◽  
Joseph Hirschfeld ◽  
...  
Keyword(s):  
Metal Binding ◽  
Large Scale ◽  
Pearson Correlation ◽  
3D Structure ◽  
Covariance Analysis ◽  
Web Based ◽  
Functional Sites ◽  
3D Space ◽  
Chi Squared ◽  
Molecular Functions

Proteins by and large carry out their molecular functions in a folded state when residues, distant in sequence, assemble together in 3D space to bind a ligand, catalyze a reaction, form a channel, or exert another concerted macromolecular interaction. It has been long recognized that covariance of amino acids between distant positions within a protein sequence allows for the inference of long range contacts to facilitate 3D structure modeling. In this work, we investigated whether covariance analysis may reveal residues involved in the same molecular function. Building upon our previous work, CoeViz, we have conducted a large scale covariance analysis among 7,595 non-redundant proteins with resolved 3D structures to assess 1) whether the residues with the same function coevolve, 2) which covariance metric captures such couplings better, and 3) how different molecular functions compare in this context. We found that the chi-squared metric is the most informative for the identification of coevolving functional sites, followed by the Pearson correlation-based, whereas mutual information is the least informative. Of the seven categories of the most common natural ligands, including coenzyme A, dinucleotide, DNA/RNA, heme, metal, nucleoside, and sugar, the trace metal binding residues display the most prominent coupling, followed by the sugar binding sites. We also developed a web-based tool, CoeViz 2, that enables the interactive visualization of covarying residues as cliques from a larger protein graph. CoeViz 2 is publicly available at https://research.cchmc.org/CoevLab/.

A Method of Structure Comparison Using Spatial Topological Patterns

2005 ◽  
Vol 277-279 ◽  
pp. 272-277
Author(s):  
Sung Hee Park ◽  
Keun Ho Ryu
Keyword(s):  
Spatial Data ◽  
Similarity Search ◽  
3D Structure ◽  
Structural Similarity ◽  
Query Protein ◽  
Data Types ◽  
Structure Comparison ◽  
3D Space ◽  
Structure Databases ◽  
Computationally Expensive

The problem of comparison of structural similarity has been complex and computationally expensive. The first step to solve comparison of structural similarity in 3D structure databases is to develop fast methods for structural similarity. Therefore, we propose a new method of comparing structural similarity in protein structure databases by using topological patterns of proteins. In our approach, the geometry of secondary structure elements in 3D space is represented by spatial data types and is indexed using Rtrees. Topological patterns are discovered by spatial topology relations based on the Rtree index join. An algorithm for a similarity search compares topological patterns of a query protein with those of proteins in structure databases by the intersection frequency of SSEs. Our experimental results show that the execution time of our method is three times faster than the generally known method DALITE. Our method can generate small candidate sets for more accurate alignment tools such as DALI and SSAP.

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